2 papers
cs.CV2026
OrthoFuse: Training-free Riemannian Fusion of Orthogonal Style-Concept Adapters for Diffusion Models
Ali Aliev, Kamil Garifullin, Nikolay Yudin +5
In a rapidly growing field of model training there is a constant practical interest in parameter-efficient fine-tuning and various techniques that use a small amount of training da…
cs.CV2025
MaterialFusion: High-Quality, Zero-Shot, and Controllable Material Transfer with Diffusion Models
Kamil Garifullin, Maxim Nikolaev, Andrey Kuznetsov +1
Manipulating the material appearance of objects in images is critical for applications like augmented reality, virtual prototyping, and digital content creation. We present Materia…